code: def _run_eval(self, dataset, data_collator, args):
      if self._type == "wp":
          self._data_collator.mlm_probability = args.mlm_probability
  
      with tempfile.TemporaryDirectory() as tmp_dir_name:
          eval_args = self._get_eval_args(tmp_dir_name, args)
          trainer = Trainer(
              model=self.model,
              args=eval_args,
              eval_dataset=dataset,
              data_collator=data_collator,
          )
          return trainer.evaluate()
  
imports: import logging
  import os
  import tempfile
  from typing import Union
  from datasets import Dataset, DatasetDict, load_dataset, load_from_disk
  import torch
  from transformers import AutoConfig, AutoModel, AutoTokenizer, Seq2SeqTrainer, Seq2SeqTrainingArguments, Trainer, TrainingArguments
  from happytransformer.args import EvalArgs, TrainArgs
  from happytransformer.fine_tuning_util import EvalResult, FistStep, ZERO_2_SETTINGS, ZERO_3_SETTINGS
label_desc: Use image node_id 14 for calling the HappyTransformer obj's underlying member method code with example usage: obj._run_eval(dataset, data_collator, args) and returns: trainer